Project

# Title Team Members TA Documents Sponsor
50 Smart Black/Whiteboard Cleaning System
Lan Li
Yichen Gu
Luke Wendt design_document0.pdf
final_paper0.pdf
photo0.jpg
presentation0.pdf
proposal0.pdf
video
Problem:
Although powerpoint is widely used in presentation nowadays, black/whiteboards are still not replaceable in some situations. After a long presentation or lecture, it is very possible for the presenter to forget cleaning the board. It is OK if the board is filled with lecture notes. But if the it is confidential information, there will be a problem. Also it is a hassle for professors to clean up the black board every time it is all written.

We would like to design a cheap black/whiteboard cleaning system. By simply waving a hand at a motion sensor mounted beside the blackboard, the brush will go from one side to the pin location you previously put on, and travel back, brushes 2 times in total. More details and functionality are presented below.

Technical Details:
This project will contain three modules:

Brush module: A vertically placed brush pressed to the board.

Motor module: Sliding rail on top and bottom of the board. 2 motors on each side of the rail to drag a wire attached to the rail, to move the brush.

Control module: This module contains three different submodules.
Wave-Clean: An ultrasonic sensor on the side of board, facing upwards. When presenter wave his/her hand at the sensor, board is cleaned.
Leave-Clean: Motion sensors around the room. When no movement for 5mins, clean the board
Partial-Clean: Presenter can put a locating pin on the rail. The brush will then move from the side to the pin, and only cleans part of the board.

It will also include a small rechargeble battery pack to power the motor.

VoxBox Robo-Drummer

Craig Bost, Nicholas Dulin, Drake Proffitt

VoxBox Robo-Drummer

Featured Project

Our group proposes to create robot drummer which would respond to human voice "beatboxing" input, via conventional dynamic microphone, and translate the input into the corresponding drum hit performance. For example, if the human user issues a bass-kick voice sound, the robot will recognize it and strike the bass drum; and likewise for the hi-hat/snare and clap. Our design will minimally cover 3 different drum hit types (bass hit, snare hit, clap hit), and respond with minimal latency.

This would involve amplifying the analog signal (as dynamic mics drive fairly low gain signals), which would be sampled by a dsPIC33F DSP/MCU (or comparable chipset), and processed for trigger event recognition. This entails applying Short-Time Fourier Transform analysis to provide spectral content data to our event detection algorithm (i.e. recognizing the "control" signal from the human user). The MCU functionality of the dsPIC33F would be used for relaying the trigger commands to the actuator circuits controlling the robot.

The robot in question would be small; about the size of ventriloquist dummy. The "drum set" would be scaled accordingly (think pots and pans, like a child would play with). Actuators would likely be based on solenoids, as opposed to motors.

Beyond these minimal capabilities, we would add analog prefiltering of the input audio signal, and amplification of the drum hits, as bonus features if the development and implementation process goes better than expected.

Project Videos